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TM3/4/5 Modeling at KNMI

TM3/4/5 Modeling at KNMI. HYMN Hydrogen, Methane and Nitrous oxide: Trend variability, budgets and interactions with the biosphere GOCE-CT-2006-037048. Atmospheric Composition research Climate Research Department KNMI. Atmospheric chemistry modeling TM Satellite Earth observation

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TM3/4/5 Modeling at KNMI

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  1. TM3/4/5 Modeling at KNMI HYMN Hydrogen, Methane and Nitrous oxide:Trend variability, budgets and interactions with the biosphere GOCE-CT-2006-037048 HYMN kick-off

  2. Atmospheric Composition researchClimate Research DepartmentKNMI Atmospheric chemistry modeling TM Satellite Earth observation OMI (PI-institute), SCIA, GOME Air Quality forecasting (new) HYMN kick-off

  3. Contents Model development KNMI: TM3 -> TM4 -> TM5 Forward modelling Methane budget studies (TM3) RETRO (TM4) New TM5 strat-trop model version Inverse modelling EVERGREEN (TM4) HYMN forward + inverse modeling activities KNMI HYMN kick-off

  4. TM3-TM4-TM5 TM modeling community (KNMI, Univ. Utrecht, Univ. Wageningen, JRC, NOAA CMDL, Univ Crete, …) TM3 (1995,..) [heritage Heimann TM2 (1991)] TM4 (2003, ..) new meteo-preprocessing TM5 trop (2003,..) zoom option TM5 trop+strat (2006,..) full-3D chemistry TM information on the web http://www.knmi.nl/~velthove/tm.html HYMN kick-off

  5. Methane budget studies (TM3) HYMN kick-off

  6. Methane lifetime 1979-1993 Dentener et al., JGR, 2003 HYMN kick-off

  7. H2O variability (ERA15) Waterdamp column (kg/m2) 3-year means Scale 0-50 kg/m2 Anomalies to the 15-year mean (Blue -5% to -15% Orange +15%) 1979-1993: increase in H2O => increase in OH => reduced growth of CH4 HYMN kick-off

  8. RETRO model intercomparison and validation (TM4) HYMN kick-off

  9. HYMN kick-off

  10. HYMN kick-off TM overestimates ozone mostly in the lower troposphere

  11. None of the models capture seasonal cycle at Barrow (Bromine chemistry) Underestimation in TM of cycle at Bermuda is partly due to relatively coarse resolution HYMN kick-off

  12. TM appears an exceptionally good model for CO HYMN kick-off

  13. HYMN Full chemistry runs TM5 trop-strat version HYMN kick-off

  14. TM5 trop-strat version Extended vertical grid up to 0.2 hPa (e.g. 44 levels) Global 3 x 2 lon-lat; zoom option to 1 x 1 49 tracers transported, 25 tracers not transported Second-order moments advection scheme Explicit chemical reaction scheme including 45 photochemical,144 gas phase and 33 heterogeneous reactions. Updated to JPL 2006. Avoids lumping of species Explicit radiative transfer module implemented for photolyisis. Actinic fluxes at selected wavelengths each time step (Landgraf and Crutzen) Full description of PSCs and NAT particle formation / sedimentation HYMN kick-off

  15. HYMN kick-off

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  18. HYMN kick-off

  19. Evergreen (TM4) HYMN kick-off

  20. Inversion SCIAMACHY data • Model: TM4 at 9x6 degrees x 25 levels • Dataset: • CH4/CO2 from Univ. Heidelberg • Year: 2004 • So far: no model CO2 correction, and averaging kernels neglected • Error assumptions • Prior emissions: 50% uniformly; spatial correlations L=1500 km • Prior initial concentrations: ~1-2%; same spatial correlations • Observations: uncorrelated, typical precision single obs. 1-2% HYMN kick-off

  21. Analysis increments HYMN kick-off

  22. Regional time series HYMN kick-off

  23. Comparison with flasks Free run Assimilation HYMN kick-off

  24. HYMN modeling at KNMI * Couplings Biosphere =>TM5 * 4D-var assimilation CH4 HYMN kick-off

  25. HYMNForward modeling • TM5, 3-hourly interpolated meteorology (release ~nov 2006) • 3x2 degrees x 44+ levels • Typically no zooming • Full troposphere-stratosphere chemistry • Recent anthropogenic emissions (EDGAR 2000) • Expected from HYMN: • significant improvements in biosphere coupling for natural emissions / deposition (CH4, N2O, H2, NO2, CO, VOCs, …) HYMN kick-off

  26. HYMNInversions • TM5 at 3x2 degrees x 34 levels • Methane emissions + chemical loss (OH from full chemistry runs) • Datasets: • Sciamachy CH4/CO2 from Univ. Heidelberg • FTIR CH4 • Surface observations • Key issues on error assumptions • On single observations or on means? e.g. to suppress large error reductions • Simulation of systematic errors? • Correlated observations? • … HYMN kick-off

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